缩小尺度
分位数
气候学
降水
环境科学
气候变化
重现期
持续时间(音乐)
计算机科学
气象学
统计
数学
地理
地质学
大洪水
海洋学
考古
文学类
艺术
作者
Elmira Hassanzadeh,Alireza Nazemi,Amin Elshorbagy
标识
DOI:10.1061/(asce)he.1943-5584.0000854
摘要
Intensity-duration-frequency (IDF) curves are commonly used in engineering planning and design. Considering the possible effects of climate change on extreme precipitation, it is crucial to analyze potential variations in IDF curves. This paper presents a quantile-based downscaling framework to update IDF curves using the projections of future precipitation obtained from general circulation models (GCMs). Genetic programming is applied to extract duration-variant and duration-invariant mathematical equations to map from daily extreme rainfall quantiles at the GCM scale to corresponding daily and subdaily extreme rainfall quantiles at the local scale. The proposed approach is applied to extract downscaling relationships and to investigate possible changes in the IDF curves for the City of Saskatoon, Canada. The results show that genetic programming is a promising tool for extracting mathematical mappings between extreme rainfall quantiles at the GCM and local scales. The duration-variant mappings were found to be more accurate than the duration-invariant relationships. Using the extracted relationships, future changes in IDF curves in the City of Saskatoon are estimated using projections obtained from the CGCM3.1 based on A1B, A2, and B1 emission scenarios. The results show that future IDF curves in the City of Saskatoon are subject to change, but the sign, magnitude, and uncertainty in the estimates of possible changes depend on the emission scenario, storm duration, return period, and mapping equations. Regardless of the emission scenario and/or the mapping relationships, the results of this study show increases in short-duration extreme rainfall with short return periods in Saskatoon. This study shows that the downscaling of extreme precipitation quantiles directly from the corresponding large-scale estimates can be an efficient approach when estimating the design precipitation values under climate change are sought.
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